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A simulated annealing-based algorithm for selecting balanced samples.
- Source :
-
Computational Statistics . Mar2022, Vol. 37 Issue 1, p491-505. 15p. - Publication Year :
- 2022
-
Abstract
- Balanced sampling is a random method for sample selection, the use of which is preferable when auxiliary information is available for all units of a population. However, implementing balanced sampling can be a challenging task, and this is due in part to the computational efforts required and the necessity to respect balancing constraints and inclusion probabilities. In the present paper, a new algorithm for selecting balanced samples is proposed. This method is inspired by simulated annealing algorithms, as a balanced sample selection can be interpreted as an optimization problem. A set of simulation experiments and an example using real data shows the efficiency and the accuracy of the proposed algorithm. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SIMULATED annealing
*ALGORITHMS
*STATISTICAL sampling
Subjects
Details
- Language :
- English
- ISSN :
- 09434062
- Volume :
- 37
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Computational Statistics
- Publication Type :
- Academic Journal
- Accession number :
- 155499531
- Full Text :
- https://doi.org/10.1007/s00180-021-01113-3